Network and customer experience monitoring solutions are widely accepted standards for the operations of carrier service provider networks across both fixed networks (e.g., Cable/Multi System Operator (MSO), IP broadband such as Digital Subscriber Line (DSL), Fiber To Home (FITH), etc.) and mobile networks (e.g., second and a half generation (2.5G), third generation (3G), fourth generation (4G), 3GPP Long Term Evolution (LTE), etc.). These systems monitor network traffic via probe devices, then process that traffic through a variety of stages to derive actionable information as it pertains to subscriber experience (quality of service, quality of experience), subscriber behavior (application usage, service usage, etc.), subscriber location, etc. In practice, actionable information may refer to statistical indicators (typically referred to as Key Performance Indicators or KPIs) that are computed from source data processed by the probes, and then made available to various different user constituents at the carrier for the purpose of driving their business process.
A few examples of KPIs include Handover Success (by node, location, etc.), Call Drop Ratio (by node, handset, etc.), Application Usage (by node, subscriber, etc.), Subscriber Count (by location, demographic, etc.), and the like.
Contemporary telecommunication network environments typically involve multiple technologies, multiple protocols, and interconnections to a wide variety of networks. More complex network environment means that the potential for problems in internetworks is high, and the source of problems is often elusive. Thus, there is a strong demand for robust diagnostic tools for troubleshooting networking failures.
Currently, there are performance monitoring tools which monitor a wide range of KPIs. While such tools are useful in identifying certain network issues, at any given moment, there may be several hundreds of KPIs that need to be analyzed over a short period of time. Thus, existing monitoring tools are limited in their diagnostic capabilities since in order to identify a root cause of any failure it is necessary to manually analyze potentially hundreds of KPIs and correlate the different outliers. This is very time consuming.
It is to be appreciated that when a network problem arises, it can be rooted anywhere in the networks. To troubleshoot network issues quickly, it is imperative to have automated analysis scheme capable of correlating multiple KPIs across multiple interfaces and protocols.